CTR Research Themes

Dynamic modelling of road traffic CTR works with microscopic and mesoscopic simulation models of road driver-vehicle units as well as hybrid combinations of such models. We have developed microscopic models of Swedish motorway traffic and calibrated and applied several other microscopic models. Our in-house mesoscopic simulator MEZZO is the platform applied in several of our research projects.

Driving behaviour We have access to the instrumented vehicle from the Traffic and Logistics division, which logs detailed behavior of its driver and that of other vehicles in front and behind the instrumented vehicle. Logged data is a basis for development of microscopic simulation models of driver-vehicle behaviour in relation to other vehicles.

Driver choice behaviour Based on Stated Preference interviews and interactive games we model driver choice of routes and departure times. Of special interest is driver reactions to information on traffic incidents.

Traffic information and control Based on traffic simulation and driver choice modelling we study the effect of traffic information on queue development and dissipation after incidents.

Effects of ITS Using microscopic simulation we evaluate effects of Intelligent Traffic Systems and especially Driver Support such as intelligent speed adaptation and lane departure warning.

Congestion charging Stockholm recently introduced a system for congestion charging in the central area. Before and after studies are used to model impacts on choice of routes and departure times. Differentiated charges over locations and time would further impact choice behaviour.

Energy consumption, emissions and noise Fuel consumption, emissions and noise from cars depend heavily on interactions in traffic causing braking and accelerations. Microscopic simulation is used to analyse network effects.

Public transport operation Where public transport operates in mixed traffic it interacts with other traffic. Mesoscopic simulation is used to study effects of bus bays, bus lanes, signal priorities and operations strategies on public transport and on other traffic.

Data collection, processing and analysis Our knowledge of traffic behaviour is based on observations collected by different sensor devices such as inductive loops, radar, cameras etc. This data needs to be fused and processed to estimate flows, speed and travel times.

OD estimation Traffic assignment and studies of alternative routes depends on knowledge of origins and destinations of vehicles and how they vary over time of day. So called OD matrices are estimated based on home surveys and traffic counts.